Overview

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Explore a comprehensive 23-hour RStudio tutorial covering a wide range of topics in data analysis, visualization, and bioinformatics. Learn to perform basic statistical analyses, create heatmaps, and utilize ggplot2 for data visualization. Dive into advanced topics such as recurrent neural networks, RNA-Seq analysis, and single-cell RNA sequencing using the Seurat package. Master essential skills like R Markdown, survival analysis, and text mining. Discover how to work with various data formats, including GEO data and TCGA cancer databases. Gain proficiency in machine learning techniques, including K-means clustering, autoencoders, and word embedding. Explore cutting-edge applications like creating chatbots, building simple blockchains, and leveraging multi-core processing for faster analyses. Ideal for beginners and intermediate R users looking to enhance their skills in data manipulation, visualization, and bioinformatics applications.

Syllabus

Running Basic Statistical Analysis in R.
How to plot a Heatmap in Rstudio, the easy way - Part 1/3.
How to use ggplot2 in R | A Beginner's RStudio Tutorial.
Recurrent Neural Network (RNN) in R | A Rstudio Tutorial on Keras and Tensorflow.
Galaxy Tutorial 2: Basic RNA-Seq Pipeline.
Gene Set Enrichment Analysis (+ R tutorial).
How to Export High Quality Image from R.
RNASeq Analysis | Differential Expressed Genes (DEGs) from FastQ.
RNASeq Analysis | Differential Expressed Genes (DEGs) from FastQ.
Clustering and Markers Identification for ScRNA-Seq | Seurat Package Tutorial.
R Markdown Tutorial for Beginners | RStudio Tutorials Part 1.
How to analyze GEO data in R?.
How to get Keras and Tensorflow running in Rstudio.
Deep Learning in Bioinformatics | Recent Advancement.
Log2 fold-change & DESeq2 model in a nutshell.
Log2 fold-change & DESeq2 model in a nutshell.
(Simplified) Linear Mixed Model in R with lme().
How to analyze 10X Single Cell RNA-seq data with R| Seurat Package Tutorial.
Make a Web App in 5 min | R Shiny Tutorial.
Survival Analysis on Cancer data | RStudio Tutorial.
Survival Analysis on Cancer data | RStudio Tutorial.
How to use gganimate in R | A RStudio Tutorial for Beginners.
Googledrive and Googlesheet4 in R | A RStudio Tutorial.
K Means Clustering and Sub-cluster Determination in Heatmap Part 2/3.
Heatmap Generation and Exporting plots as hi-res PNG - Part 3/3.
How to Plot a 3D graph | Plotly Tutorial in Rstudio.
S3 and S4 Object in R | Object Oriented Programming and Bioconductor.
You will need this for your meta analysis | Forest plot in RStudio.
Text Mining with R - Part 1 | Importing PDF and Text Detection.
How to check the frequencies of gene mutations in TCGA cancer database [R].
Creating a Heatmap in R | ComplexHeatMap tutorial p1.
Word Embedding with Keras: A RStudio Tutorial.
R Markdown Tutorial for Beginners | RStudio Tutorials Part 2.
Subset Clusters in Seurat.
Autoencoder in RStudio Tutorial.
Comparing scRNA-Seq | Suerat Integration Analysis (Brief).
Summarized Experiment (se) Object from Bioconductor.
Gene Set Enrichment Analysis| GSEA algorithm.
Data Transformation with R using dplyr part 1/6.
PyTorch is now on R.
Build a Telegram Chat Bot in R | Simple RStudio Project Tutorial.
Efficient Loopsing in R | Rstudio FOR Loop Tutorial.
I Force AI to read research paper 100 times | Text mining in R.
How to Build A Simple Neural Network in R.
Annotations on Heatmaps | ComplexHeatMap tutorial.
Cancer Somatic Mutation Analysis | MAFtools R Package.
GFF3 File Format | Clearly Explained.
TCGA Biomarkers Identification using Machine Learning | Complete Walkthrough.
Make your Analysis 4x faster | Multi core processing with R.
How to Make a Simple Blockchain | R Tutorial.
DEG isolation using limma voom | A Rstudio Tutorial.
Oncoprint Walkthrough (Essential).
How to create your own package in R?.
Data manipulation in R (For Bioinformatics)| R tutorial | For beginner.
Joining Multiple Heatmaps | ComplexHeatMap tutorial.
It is better than Microsoft Word | Writing in R Markdown.
Why R Programming is better (For me) ?.
Visualize a Neural Network | ggplot2 & Keras in RStudio.
R Data Project Best Practice.
Why R uses so much memory ? Probably.
How to know if two genes are similar? | Semantic Similarity Explained.
How to do data Imputation with RStudio.
16s rRNA Sequencing Analysis and Visualization.